Outlook for Combined TMI–VIRS Algorithms for TRMM: Lessons from the PIP and AIP Projects

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Abstract
The status of current rainfall-retrieval techniques by satellite radiometry has been evaluated by recent international algorithm intercomparison projects. As a general result, passive microwave techniques perform superiorly for instantaneous applications over oceans, while infrared or combined infrared–microwave techniques show improved monthly rainfall accumulations, mainly due to the high temporal sampling by geosynchronous observations. Merging microwave, visible, and infrared imagery data available on the same satellite such as the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) and the Visible Infrared Scanner (VIRS) provides further potential for the improvement of instantaneous retrievals. A case study is shown that demonstrates the stepwise degradation of information contained in the microwave signals when three-dimensional cloud effects and realistic antenna patterns are simulated for a convective cloud obtained from Doppler polarization radar soundings. Simultaneous visible and infrared data may contribute mainly to better rain-regime classification, in particular when sophisticated cloud identification techniques and cloud parameter retrievals are incorporated. Although the beam-filling problem is not solved by the TMI–VIRS combination alone, some other progress, for example, concerning better coastline treatment, is shown. With respect to monthly products and the climatologically important observation of diurnal rainfall variations, the TRMM sensor combination will provide a calibration standard to be applied to geosynchronous sensors.

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